Risk Management
A.Y. 2023/2024
Learning objectives
At the end of the course, the student will possess an adequate mathematical terminology, learned the main quantitative and computational tools to be able to work in the risk management unit of a bank or insurance company.
Expected learning outcomes
At the end of the course, the student will know the basic elements of the Basel and Solvency regulatory frameworks for banks and insurance companies; will possess an adequate mathematical terminology and learned the main quantitative tools related to the study of risk variables and measures in quantitative risk management; will be able to recognize statistically the presence of an elliptical or heavy-tailed distribution and determine its influence on a risk portfolio; will be able to code a software for the computation of the capital reserve needed by a financial institution to comply with the above regulatory frameworks; will be aware of the basic quantitative tools to perform the stochastic aggregation of various typologies of risks.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
Overview of Basel 2, Basel 3 and Solvency 2. Basic Concept in Risk Management: Risk Measures (VaR and ES).
Light tailed versus Heavy tailed distributions. Regularly varying distributions, EVT: the POT method.
Modeling dependence with copulas.
Multivariate Modelling: ''if Only the World Were Elliptical'' - Coherent Measures of Risk .
Standard methods for Market Risk .
Risk Aggregation and Model Uncertainty.
Seminar by a practitioner
Light tailed versus Heavy tailed distributions. Regularly varying distributions, EVT: the POT method.
Modeling dependence with copulas.
Multivariate Modelling: ''if Only the World Were Elliptical'' - Coherent Measures of Risk .
Standard methods for Market Risk .
Risk Aggregation and Model Uncertainty.
Seminar by a practitioner
Prerequisites for admission
Elementary Probability and Integration
Teaching methods
Classrooms with applications in R.
Teaching Resources
TEXTBOOK:
AJ McNeil, R Frey and P Embrechts,
Quantitative Risk Management: Concepts, Techniques, Tools. Revised Edition.
Princeton University Press, Princeton, 2015;
EXTRA MATERIAL will be provided by the instructor
AJ McNeil, R Frey and P Embrechts,
Quantitative Risk Management: Concepts, Techniques, Tools. Revised Edition.
Princeton University Press, Princeton, 2015;
EXTRA MATERIAL will be provided by the instructor
Assessment methods and Criteria
Written exam with some exercises that require to write a few simple lines of R code. Each exercise reports the relative score. A workbook and exams from previous years are provided.
SECS-S/06 - MATHEMATICAL METHODS OF ECONOMICS, FINANCE AND ACTUARIAL SCIENCES - University credits: 6
Lessons: 40 hours
Professor:
Puccetti Giovanni
Professor(s)